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Environ Monit Assess

DOI 10.1007/s10661-008-0724-5

Evaluating forest fragmentation and its tree community

composition in the tropical rain forest of Southern WesternGhats (India) from 1973 to 2004

A. Giriraj · M. S. R. Murthy · C. Beierkuhnlein

Received: 19 February 2008 / Accepted: 23 December 2008© Springer Science + Business Media B.V. 2009

Abstract A majority of the research on forest

fragmentation is primarily focused on animal

groups rather than on tree communities because

of the complex structural and functional behav-

ior of the latter. In this study, we show that

forest fragmentation provokes surprisingly rapid

and profound alterations in tropical tree commu-

nity. We examine forest fragments in the tropi-

cal region using high-resolution satellite imagery

taken between 1973 and 2004 in the Southern

Western Ghats (India) in relation to landscapepatterns and phytosociological datasets. We have

distinguished fragmentation in six categories—

interior, perforated, edge, transitional, patch, and

undetermined—around each forested pixel. Fur-

thermore, we have characterized each of the frag-

ment class in the evergreen and semi-evergreen

forest in terms of its species composition and

richness, its species similarity and abundance, and

its regeneration status. Different landscape met-

rics have been used to infer patterns of land-use

changes. Contiguous patches of >1,000 ha covered

A. Giriraj (B) · C. BeierkuhnleinDepartment of Biogeography, Universität Bayreuth,Bayreuth, 95440, Germanye-mail: gudugiri@yahoo.com

M. S. R. MurthyForestry and Ecology Division, National RemoteSensing Centre, Hyderabad 500 037, India

90% of evergreen forest in 1973 with less porosity

and minimal plantation and anthropogenic pres-

sures; whereas in 2004, the area had 67% forest

coverage and a high level of porosity, possibly

due to Ochlandra spread and increased planta-

tions which resulted in the loss of such contiguous

patches. Results highlight the importance of land-

scape metrics in monitoring land-cover change

over time. Our main conclusion was to develop an

approach, which combines information regarding

land cover, degree of fragmentation, and phy-tosociological inputs, to conserve and prioritize

tropical ecosystems.

Keywords Fragmentation ·

Kalakkad Mundanthurai tiger reserve ·

Tropical forests · Land-cover change ·

Landscape pattern · Remote sensing

Introduction

Forest fragmentation in tropical rain forests is

considered as one of the greatest threats to global

biodiversity because these forests are the most

species-rich of terrestrial ecosystems (Myers 1986;

Whitmore and Sayer 1992; Armenteras et al.

2003). The complex process of fragmentation and

forest loss is a common phenomenon in tropi-

cal forests, and apart from forest degeneration,

also brings about several physical and biological

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Environ Monit Assess

changes in the forest environment. (Skole and

Tucker 1993; Serio-Silva and Rico-Gray 2002;

Cordeiro and Howe 2003; Jha et al. 2005). These

two processes may have negative effects on

biodiversity, by increasing isolation of habitats

(Debinski and Holt 2000), endangering species,

modifying species’ population dynamics (Watsonet al. 2004), and expanding at the expense of 

interior habitat (Mace et al. 1998). Consequently,

this is a leading cause for the decline and loss of 

species worldwide and has been a topic of consid-

erable research and review (Noss 1996; Laurance

et al. 1998a, b, 2002).

The effects of fragmentation on species rich-

ness tend to have sunk in the probability of suc-

cessful dispersal and establishment (Gigord et al.

1999; Cordeiro and Howe 2003; Girira j 2006) as

well as reduced the capacity of a patch of habi-tat to sustain a resident population (Iida and

Nakashizuka 1995). The ecological consequences

of fragmentation may differ depending on the

patterns of spatial configuration imposed on a

landscape and how it varies both temporally and

spatially (Ite and Adams 1998; Armenteras et al.

2003). Therefore, an understanding of the rela-

tionship between landscape patterns and the eco-

logical processes influencing the distribution of 

species is required by resource managers to pro-

vide a basis for making land-use decisions (Turneret al. 2001).

Land use/land cover is a fundamental variable

that impacts the forest fragmentation and isola-

tion of habitats, which is being linked with human

and physical environments. While the impor-

tance of human activities is widely recognized,

the relative influence of human activities on en-

vironmental factors is less understood. However,

land-cover maps indicate only the location and

type of vegetation, and further processing is

needed to quantify and map forest fragmentation

(Turner and Gardner 1991; Gustafson 1998). To-

day, remote sensing is being considered an excel-

lent tool for the analysis and effective monitoring

of forest fragmentation. Several studies have used

remote sensing to map patterns of forest frag-

mentation and to analyze the rates of forest-cover

change in the tropics and elsewhere (Vogelmann

1995; Riitters et al. 2000, 2002; Wickham et al.

2000, 2007). Our objective is to map and compare

patterns of forest fragmentation in temporal time

by using a fragmentation model (Riitters et al.

2000, 2002; Wade et al. 2003) that distinguishes

between the different levels of fragmentation. Our

study also identifies areas of large interior forest

and isolated patches for conservation priorities.

Our study also helps to identify and prioritize re-gions using phytodiversity information from direct

measurement of impacts.

Study area

The Kalakkad Mundanthurai Tiger Reserve

(KMTR) is located at the southern end of the

Western Ghats, Tamil Nadu, India (Fig. 1) and

lies between 8◦21–8◦52 N latitude and 77◦10–

77◦33 E longitude in the biogeographic provinces4.14.4 (Deccan thorn forest) and 4.1.1 (Malabar

rainforest) (Udvardy 1975). The area falls into two

districts, namely, Tirunelveli and Kanya Kumari

of Tamil Nadu and bounded in the west by the

state of Kerala.

KMTR, the second largest protected area in the

state of Tamil Nadu covers an area of 907 km2

with hills towering to majestic heights ranging

from 100 to 1,880 m (Agasthiar peak). Agasthya-

malai hills, at the southern end of the Western

Ghats, are known for high species diversity, har-boring 2,000 flowering plant species with 7.5%

endemism (Henry et al. 1984). The mid-elevation

zone (700–1,400 m) is the tropical wet ever-

green forest of the Cullenia–Mesua–Palaquium

series (Pascal 1988). The topography is rugged

with numerous perennial hill streams originating

from the tropical rainforest areas in the upper

slopes, and they confluence to form major rivers

such as the Tambiraparani, Manimuthar, and

Ramanadhi, which support the agricultural econ-

omy of millions in the adjoining plains. The forests

of the reserve include the catchment area of 

the Manimuthar, Kodayar, Servalar, and Karaiar

dams. The climate of the area is typically with

a minimum rainfall of 1,200 mm to a maximum

of 5,000 mm. Annual average temperature ranges

from 13.5◦C in the evergreen to 23◦C in the decid-

uous forests. Dry period ranges from 3 to 5 months

and number of rainy days is in the order of 89–

92 days (Pascal 1982).

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Fig. 1 Map showing thegeographic positionof KMTR, SouthernWestern Ghats, inTirunelveli andKanykumari districtof Tamil Nadu state,south India

Forest types such as tropical evergreen, semi-

evergreen, moist deciduous, dry deciduous, grass-

lands, and secondary succession exist in the study

area. The dominant evergreen tree species are

Cullenia exarillata, Mesua ferrea, Palaquium ellip-

tium, Myristica dactyloides, and Aglaia bourdil-

lonii and deciduous species includes Anogeissus

latifolia, Terminalia chebula, and Terminalia bel-

lirica. The major invasive species include Lantana

camara, Ageratum conyzoides, and the Eupatorium

species.

History of changes in KMTR

The evergreen forests of the KMTR have a long

history of change in forest-cover and land-use

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type over the last 250 years (Caldwell 1989).

Ramesh et al. (1997) quantified a significant loss

of biologically rich areas between 1960 and 1990:

85.6 km2 to plantations, 42 km2 to encroachment,

and 36.4 km2 to reservoirs. A total of 28 enclaves

have been identified within the KMTR (Ali and

Pai 2001). A total of 189 eco-development villagesare in the immediate vicinity of the park at the

eastern perimeter in a 5-km broad strip. Ecolog-

ical damages due to forest fire, invasion of reeds,

and erosion are some of the major causes, which

might have led to change in floristic composition,

regeneration, and loss of endemics.

Materials and methods

Forest type classification using satellite data

Cloud-free satellite data of LANDSAT Multi-

spectral Scanner (MSS) of March 1973 cover-

ing path and row 154/54 was obtained from the

U.S. Geological Survey, USA, and IRS-1C Lin-

ear Imaging Self Scanner (LISS)-III satellite data

of 19 March 2004 covering path and row 101/68

was obtained from the National Remote Sensing

Agency, Hyderabad. LANDSAT-MSS data with

a spatial resolution of 80 m and spectral bands

(B1 0.5–0.6, B2 0.6–0.7, B3 0.7–0.8, and B4 0.8–1.1 μ m), and IRS-P6 LISS-III data with a spatial

resolution of 24 m and spectral bands (B2 0.52–

0.59, B3 0.62–0.68, B4 0.77–0.86, and B5 1.55–

1.70 μ m) was analyzed in the present study.

Initially, evergreen and semi-evergreen for-

est patches of 2004 (LISS-III) was characterized

using supervised classification technique based

on the information of terrain, topography, and

species database collected during landscape bio-

diversity characterization program for Western

Ghats (Dutt et al. 2002). Based on the identi-

fied 2004 evergreen and semi-evergreen patches,

an area of interest (AOI) was selected from the

evergreen and semi-evergreen vegetation patch

of 1973, assuming that these patches of 2004 had

remained unchanged from 1973. Likewise, all the

other land-cover classes were classified to gen-

erate vegetation and land-cover map of KMTR.

After the completion of preclassification, misclas-

sified areas were observed and reclassified using

small AOI or through interactive editing for im-

proved accuracy. The maximum likelihood algo-

rithm (Lillesand and Kiefer 2000) was used to

classify these patches. The classified vegetation

and land-cover map were randomly checked in

the field with Global Positioning System (GPS)

points. The overall accuracy stands at 85% witha kappa statistics of 0.81. Finally, IRS LISS-III

dataset were resampled to 80 m (equivalent to

MSS) to facilitate comparison.

Landscape analysis

Landscape is defined as “an aggregation of het-

erogeneous elements, which interact with each

other.” Landscape has three intrinsic properties:

structure, function, and change. These can be ex-

plained in terms of porosity, fragmentation, patchdensity, patchiness, interspersion, juxtaposition,

contagion, etc. (Forman and Godron 1986). In

the present study, the following landscape metrics

have been studied to assess forest fragmentation

patterns.

Fragmentation modeling

Land-cover map with a spatial resolution of 80 m

was used to characterize the fragmentation levels

around the evergreen and semi-evergreen forestspixel. To perform the fragmentation calculations,

we used a “moving window” algorithm developed

by Riitters et al. (2000). The model was designed

to identify patterns of forest fragmentation us-

ing coarse- and fine-scale resolution land-use and

land-cover information.

To implement the fragmentation model, the

size of the analysis window had to be determined.

After considering the resolution of data, delin-

eation of the forest features, and practical assess-

ment of the various window sizes, a 5 × 5 window

was found to maintain an adequate representation

of the proportion (Pf) of pixels in the window

and also to represent the interior forest at an

appropriate level. The window was centered on

each land-cover pixel (forested or not), a fragmen-

tation score was calculated for the window, and

the result was assigned to the center pixel. Maps

of four indices were produced for each forest

classes to characterize forest fragmentation by

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Fig. 2 Forest fragmentation categories from local mea-surements of Pf and Pff (adapted from Riitters et al. 2000)

anthropogenic pixels (Pfa), forest fragmentation

by nonforest natural land-cover pixels (Pfn), over-

all forest connectivity (Pff), and forest area den-

sity (Pf). The computations are illustrated in detail

in Riitters et al. (2000), as Pf was the proportion of 

the forests in the analysis window and Pff was the

ratio of the number of adjacent (cardinal direc-

tions only) pixel pairs for which both pixels were

forest, to the number of adjacent pixel pairs where

either one or both pixels were forest. Figure 2shows the classification model that identifies six

fragmentation categories: (1) interior, for which

Pf  = 1.0; (2) patch, Pf  < 0.4; (3) transitional,

0.4 < Pf < 0.6; (4) edge, Pf > 0.6 and Pf–Pff > 0;

(5) perforated, Pf > 0.6 and Pf–Pff  < 0, and (6)

undetermined, Pf > 0.6 and Pf = Pff.

Using the results from the forest fragmenta-

tion model, further research was conducted to

produce maps, which identify the state of forest

fragmentation of a specified region. The purpose

for the forest fragmentation index was to provide

a quick means to assess the extent of forest frag-

mentation within a region and to track trends in

forest fragmentation to identify areas that would

benefit from possible reforestation. Different in-

dexes were used to generate forest fragmenta-

tion, e.g., total forest proportion (TFP), forest

continuity (FC), and weighted forest area (WFA)

(Vogelmann 1995; Wickham et al. 1999; Civco

et al. 2002).

Patch metrics

Patch size, number, and shape Once the classi-

fied forest patches were prepared using satellite

data, they were vectorized in geographic informa-tion system domain to characterize the patches.

The information on patch size and number wasextracted from the vectorized classified data. A

minimum of 3 × 3 pixel window was set for

patch analysis. A simple measure of patch shape

is the perimeter-to-area (PA) ratio. This measure

is often standardized so that the most compact

possible form, either square or circle, is equal to

1. Higher perimeter value indicates increase of 

edge effect, an ecologically undesirable influence

on most species population and communities.

Contagion index The contagion metric was first

proposed by O’Neil et al. (1988) and later by

several others (Graham et al. 1991; Gustafson

and Parker 1992; Li and Reynolds 1993). It is a

measure of clumping or aggregation of patches.

It is also used as an indication of the degree of 

landscape fragmentation.

Fractal dimension Fractal dimension (FD) has

been used for measurement, simulation, and as

a spatial analytic tool in the mapping sciences(O’Neil et al. 1988; De Cola 1989). Changes in the

FDs of the remote sensing images have implica-

tions on changes in the environmental conditions

(Lam and Ouattrochi 1992). A number of studies

have found that the FD of the landscape varies

according to the type of land use (O’Neil et al.

1988; De Cola 1989).

Patch per unit  Patch per unit (PPU) is low when

the landscape is not fragmented. As the landscape

becomes more fragmented, the PPU increases(Frohn 1998).

Landscape shape complexity As an alternative

to the FD for quantifying patch shape complex-

ity, patch shape complexity (SqP) has been in-

troduced (Frohn 1998). The SqP considers the

perimeter–area relationship for raster data struc-

tures and normalizes the ratio of perimeter to area

to a value between 0 and 1.

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Landscape shape index The landscape shape in-

dex (LSI) provides a standardized measure of 

total edge or edge density that adjusts for the

size of the landscape. Because it is standardized,

it has a direct interpretation in contrast to total

edge. LSI is a measure of patch aggregation or

disaggregations. LSI increase leads to an increasein disaggregation.

Floristic data analysis

A total of 95 sample points were chosen for phy-

tosociological data collection. The samples points

were randomly distributed covering different frag-

mented classes to understand their species rich-

ness, diversity, and dominance. While sampling,

field inventory fragmented categories were com-

bined as interior, patch, and other classes (transi-tional, edge, perforated, and undetermined). The

geographic coordinates of the sample points were

generated using the hand-held GPS; the locations

for the field plots were reached. Plots (0.1 ha)

were laid on the ground at the corresponding lo-

cation. The field work was conducted from March

2004 to June 2004. Tree girths were measured

at 1.3 m from the ground. Specimens identified

were confirmed in the herbarium of the Botan-

ical Society of India, Coimbatore and the Rap-

inat Herbarium, Tiruchirapalli. Of the total 95plots, 68 plots were evergreen fragments (37, 19,

and 12, respectively) and 27 plots were in the

semi-evergreen fragment class (15, five, and seven,

respectively).

Results

Vegetation types

Major phenological and land-cover types for the

KMTR region between 1973 and 2004 are given in

Table 1. The changes in vegetation cover based on

digital classification shows a significant decrease

of evergreen forest mostly to semi-evergreen for-

est types (Table 2). Of the total area covered

by natural vegetation (857 km2), the evergreen

and semi-evergreen forest occupied around 60%

of the area. In 1973, evergreen forest consti-

tuted 316 km2, followed by semi-evergreen hav-

Table 1 Vegetation and land-cover distribution for theKMTR, Southern Western Ghats (India)

S. no. Types 1973 2004

Phenelogical types

1 Evergreen 316.72 185.49

2 Semi-evergreen 194.40 268.10

3 Moist deciduous 143.59 135.46

4 Dry deciduous 38.95 96.305 Dry evergreen 136.14 57.55

6 Grassland 27.36 75.14

Subtotal 857.16 818.04

Other land-cover types

7 Shrubs 1.11 17.42

8 Ochlandra 13.56 23.82

9 Orchards 2.33 16.50

10 Fallow/barren 10.04 10.01

11 Water 15.22 21.67

12 Shadow 6.97 0.00

13 Cloud 1.07 0.00

Grand total 907.46 907.46

ing 194 km2. In 2004, the evergreen forest has

degraded to 185 km2 (i.e., it has lost almost 40%

of land cover whereas semi-evergreen forest has

increased by 36% to 268.1 km2).

Landscape analysis

Forest fragmentation

The area under fragmentation in the evergreen

forest type showed significant changes between

1973 and 2004 (Table 3). While the interior

category decreased from 113.90 km2 (36%) to

23.27 km2 (12%) and perforated category de-

creased from 85.0 to 23.7 km2, the other categories

shows significant increase in fragmentation (patch

category 14.82 to 25.3 km2; edge category 66.8

to 80.15 km2). There appear to be no significant

change in the transitional category. In case of 

semi-evergreen, almost all categories except the

perforated and transitional category showed sig-

nificant increase (Table 3). Like evergreen forests,

in these forests, also the transitional category did

not show any significant change during 1973–2004.

The perforated category showed a decrease from

60.4 to 31.7 km2. The TFP of the evergreen forest

has decreased by 40%, while the semi-evergreen

patch showed an increase of TFP by 36%. A

similar trend is also seen in the WFA values of 

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Table 2 Change matrixfor the KMTR between1973 and 2004, SouthernWestern Ghats (India)

1973 Evergreen Semi-evergreen Others Total

2004

Evergreen 163.31 124.74 28.67 316.72

Semi-evergreen 21.02 119.19 54.20 194.40

Others 1.16 24.17 371.02 396.34

Total 185.49 268.10 453.88 907.46

evergreen and semi-evergreen forests. Evergreen

FC decreased by 88.4%, while the semi-evergreen

FC was seen to increase by 77% (Table 4).

Patch analysis

The patch size and distribution for the period

of 1973–2004 shows a relative decrease in the

number of smaller patches and an increase in the

number of larger patches in the evergreen as wellas the semi-evergreen type (Tables 5 and 6). In

1973, patches less than 50 ha constituted 7% (131

patches) while those in the 100–500 ha constituted

6.22% (nine patches) of the total evergreen area.

Contrastingly, in 2004, the patches less than 50 ha

constituted 9.77% (110 patches) and those in the

100–500 ha made up 12.53% (ten patches) of 

the evergreen forest area. Interestingly, 90% of 

the patches were greater than 1,000 ha in 1973

(three patches), compared to just 67% in 2004

(four patches). Similarly, in the semi-evergreenforest category, the 1973 data for patches greater

than 1,000 ha showed 23% (three patches) while

the 2004 data for large area showed 60% (three

patches). The results revealed that the distribution

of patches could be categorized into four different

patterns, namely, large areas covered by lesser

number of patches (evergreen forest of 1973),

small areas covered by fewer number of patches

(evergreen forest of 2004), small areas covered by

a large number of patches (semi-evergreen forest

of 1973), and small areas covered by the least

number of patches (semi-evergreen forest of 2004)

as seen in Tables 5 and 6.Patches having a PA ratio of  <0.015 in 1973

were 51% (i.e., 80 patches) compared to just 30%

in 2004 (i.e., 42 patches), indicating the contiguity

of large patches with lesser perimeter (Tables 5

and 6). In 2004, the tendency toward higher PA

ratio (>0.025) was 37.41% (52 patches), compared

to 10.83% (17 patches) in 1973. It is observed

that complex shapes have increasingly higher PA

ratios.

In the case of evergreen forests, FD increased

from 1.32 to 1.35, while in case of semi-evergreen,it was constant at 1.37 (Tables 5 and 6). The

PPU, which is an indication of clumping, showed

an increase in the case of evergreen forest type

Table 3 Forestfragmentation categoriesfor the evergreen andsemi-evergreen(1973–2004) in KMTR of Southern Western Ghats(India), area in square

kilometers

Values in parenthesesindicate the percentagevalue for each fragmentclass

Sl 1973 2004

Evergreen forest

1 Interior 113.9 (35.96) 23.27 (12.35)

2 Patch 14.78 (4.67) 25.33 (13.44)

3 Transitional 32.95 (10.40) 31.6 16.76)

4 Edge 66.88 (21.12) 80.15 (42.52)

5 Perforated 85.00 (26.84) 23.73 (12.59)

6 Undetermined 3.12 (1.01) 4.4 (2.33)

Total 316.72 188.49

Semi-evergreen forest

1 Interior 10.47 (5.39) 29.35 (11.07)

2 Patch 29.56 (15.21) 35.24 (13.29)

3 Transitional 49.55 (25.49) 49.42 (18.64)

4 Edge 44.16 (22.72) 115.28 (43.49)

5 Perforated 60.41 (31.08) 31.69 (11.95)

6 Undetermined 0.25 (0.13) 4.12 (1.55)

Total 194.40 265.10

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Table 4 Forest fragmentation conditions based on TFPand FC for evergreen and semi-evergreen (1973–2004) inKMTR of Southern Western Ghats (India)

Evergreen Semi-evergreen

1973 2004 1973 2004

TFP 0.355 0.212 0.218 0.298

WFA 274.38 147.06 150.28 207.19

FC 0.043 0.005 0.002 0.009

(1.18E - 07 to 2.17E - 07), while in case of 

semi-evergreen, the PPU showed a slight decrease

from 2.44E - 07 to 2.31E - 07. The SqP in the

case of evergreen forests showed an increase from

0.956 to 0.965, while for semi-evergreen it showed

a marginal increase from 0.973 to 0.974. The de-

gree of fragmentation indicated by the contagionmatrix showed a slight decrease in the case of 

evergreen forest (0.452 to 0.450), while in case of semi-evergreen, there was an increase from 0.457

to 0.469.

Phytosociological analysis

Based on field data from 95 sample points of 

0.1 ha, the tree species richness in evergreen and

semi-evergreen showed a total of 339 species from

184 genera distributed in 62 families with a stand

density of 560 stems ha−1 from 5,317 individuals

(Table 7). Of the total 297 tree species observedin the evergreen forest, the interior fragment class

had a tree species richness of 204 with a stand den-

sity of 705 stems ha−1 and 6.27H species diversity.

While the patch class had 173 tree species with a

stand density of 473 stems ha−1, other fragment

classes in total had only 126 tree species and a

stand density of 435 stems ha−1 (Fig. 3). Con-

trastingly, the semi-evergreen forests of interior

fragment class had 176 tree species with a stand

density of 589 stems ha−1 and a high species di-

versity of 6.55. Patch and other fragment classesof the semi-evergreen class had a tree species

richness of 61 and stand density of 392 and 297

stems ha−1 with varying diversity 5.30 and 5.22,

respectively. Endemic evergreen tree species in

the interior fragment class had high species rich-

ness (76) and high stand density (286 ha−1) while,

in contrast, the saplings of these systems had 160

individuals of 45 species.

Girth–class distribution for the different frag-

mented classes showed a uniform decrement with

increase in forest fragmentation (Fig. 4). Ever-green forests of the interior category had uniform

distribution in its frequency and abundance when

compared to the fragmented category, which

clearly explains the intactness and contiguity. The

total number of plant families for the study site

was 57. Euphorbiaceae, with 39 species, constitute

an important family of canopy trees dominating

the forest locally. Lauraceae (32), Rubiaceae (27),

and Meliaceae (18) were the families represented

next best, followed by Moraceae (18), Ebenaceae

(17), and Myrtaceae (14).A major dominance of  Cullenia exarillata was

observed in all the fragment categories of ever-

green forests, while the interior class of the ever-

green forests had a typical community structure

Table 5 Patchcharacteristics and otherlandscape metricsanalyzed for theevergreen and

semi-evergreen forests of KMTR, SouthernWestern Ghats (India)

Numbers withoutparentheses indicate thepercentage of evergreenforest, while numbers inparentheses indicate thenumber of patches

Sl Parameters Evergreen Semi-evergreen

1973 2004 1973 2004

1 Area (km2) 290.25 150.14 193.45 229.89

2 Number of patches 157 139 361 199

3 Patch density 0.54 0.93 1.87 0.87

5 Patch size (ha)

<50 7.05 (131) 9.77 (110) 24.52 (292) 10.54 (171)

50 to 100 3.18 (14) 6.58 (14) 10.37 (29) 2.81 (10)

100 to 500 6.22 (9) 12.53 (10) 32.83 (34) 12.14 (11)

500 to 1,000 0.00 3.33 (1) 8.87 (3) 13.90 (4)

>1,000 90.60 (3) 67.79 (4) 23.41 (3) 60.61 (3)

6 Perimeter/area ratio

<0.015 50.96 (80) 30.22 (42) 48.75 (176) 14.57 (29)

0.016–0.020 38.22 (60) 32.37 (45) 41.00 (148) 39.20 (78)

>0.025 10.83 (17) 37.41 (52) 10.25 (37) 46.23 (92)

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Table 6 Patch characteristics and other landscape metrics analyzed for the evergreen and semi-evergreen forests of KMTR,Southern Western Ghats (India)

Type LSI Patch cohesion Contagion D PPU SqP

Evergreen

1973 16,997.04 99.9976 0.452 1.32 1.1764E - 07 0.965

1998 16,373.33 99.9952 0.450 1.36 2.1697E - 07 0.966

Semi-evergreen

1973 16,997.04 99.9961 0.457 1.38 2.4433E - 07 0.9731998 16,373.33 99.9967 0.460 1.38 2.3063E - 07 0.974

dominated by Cullenia–Myristica–Mesua– Aglaia

and Palaquium. This dominance was not seen

in the case of the highly fragmented systems.

These classes were made up of both primary

and secondary species like Dimocarpus, Diospy-

ros, Antidesma, and Mallotus. On the other hand,

Mesua, Dimocarpus, Xanthophyllum, and Schle-ichera species dominate semi-evergreen forests

of the interior fragment. Other fragmented cate-

gories of the semi-evergreen forest include domi-

nant species such as Dimocarpus, Kingiodendron,

Filicium, Hopea, and Scolopia (Table 8).

Discussion and conclusions

The method presented in this paper can be eas-

ily extended to calculate fragmentation of any

land-cover type for its quantification and impact

assessment. It is also clearly independent of the

scale and pixel size of analysis. Raster land-coverdata of any resolution can be used directly. Dif-

ferent window sizes may also be used and may

produce significantly different results (see Riitters

et al. 1997, 2000, 2002). As such, it is impor-

tant that decision makers apply the model at

Table 7 Consolidated phytosociological analysis for the evergreen and semi-evergreen forests in different fragmentcategories identified in the Southern Western Ghats (India)

Fragment Total Species No. of Species Endemics Stand density Basal area

class plots richness individuals diversity (species/individuals) (ha−1) (m2/ha)

Evergreen forest

Tree analysis

Interior 37 204 2,609 6.27 76 1,057 705 64.1

Patch 19 173 898 6.53 61 283 473 39.7

Others 12 126 522 6.12 53 183 435 47.0

Total 68 297 4,029 106 1,523 593 54.3

Sapling analysis

Interior 31 105 352 6.13 45 160 114 0.3

Patch 16 117 367 6.31 45 141 229 0.7

Others 10 78 208 5.87 37 79 208 0.6

Total 57 182 927 76 380 163 0.4

Semi-evergreen forest

Tree analysis

Interior 15 176 884 6.55 60 345 589 47.8

Patch 5 61 196 5.30 24 75 392 27.3

Others 7 61 208 5.22 16 68 297 30.3

Total 27 209 1,288 66 488 477 39.4

Sapling analysis

Interior 15 95 206 6.11 35 85 137 0.4

Patch 5 50 107 5.37 20 45 214 0.6

Others 7 57 158 5.26 21 44 226 0.5

Total 27 137 471 50 174 174 0.5

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0

200

400

600

800

1000

1200

1400

1600

1800

Interior Patch Other classes

Fragment Class

   S   t  a  n   d   d  e  n

  s   i   t  y   (   h  a

  -   1   )

SEG-Sap

SEG-Tree

EG-Sap

EG-Tree

Fig. 3 Tree and sapling stand density based on the numberof individuals and its fragment class for the evergreen and

semi-evergreen forests in KMTR, Southern Western Ghats(India)

a scale appropriate to the policy under devel-

opment. Reporting units of any size may be

used to summarize fragmentation, which allows

for multiscale assessments. Globally, researchers

0

200

400

600

800

1000

1200

1400

3   0   -  6    0   

9   0   -  1   2   0   

1   5    0   

-  1   8   0   

2   1   0   

-  2   4   0   

2   7    0   

-  3   0   0   

3   3   0   

-  3   6    0   

3   9   0   

-  4   2   0   

>  4   5    0   

   N  o .  o   f   I  n   d   i  v   i   d  u  a   l  s

0

100

200

300

400

500

3   0   -  6    0   

9   0   -  1   2   0   

1   5    0   -  1   8   0   

2   1   0   -  2   4   0   

2   7    0   -  3   0   0   

3   3   0   -  3   6    0   

3   9   0   -  4   2   0   

>  4   5    0   

Girth class (cm)

   N  o .  o   f   I  n   d   i  v   i   d  u  a

   l  s

Interior

Patch

Others

Fig. 4 Forest stand structure based on tree girth frequencyin various size classes for the fragment category in KMTR,Southern Western Ghats (India)

address the patterns of forests fragmentation

using land-cover maps (Robinson et al. 1995;

Riitters et al. 2000; Wickham et al. 2000, 2007;

Southworth et al. 2002, 2004), and at the lo-

cal scale, address the species loss due to forest

fragments (Chittibabu and Parthasarathy 2000;

Benitez-Malvido and Martinez-Ramos 2003; Zhuet al. 2004; Laurance et al. 2006; Laurance and

Luizão 2007). Very few studies have been con-

ducted in tropical forests to integrate process

and function through a combination of land-cover

maps derived from satellite image and phytosoci-

ological datasets (Jha et al. 2005; Roy et al. 2005;

Giriraj 2006). Our study identified the needs of 

such approaches, which could be a useful tool

to develop a combined strategy for protection,

restoration, and management of forests—a strat-

egy that includes opportunities for sustainableconservation of biological diversity.

Our findings from the fragmentation model in

KMTR arise from a study of anthropogenic activ-

ities like encroachment, plantations, and selective

felling or natural changes like invasion of reed

brakes. We observed an increase in fragmentation

over time, which might have led to an increase

in the isolation of evergreen patches. Decreased

patch size might have led to a reduction in the

size of populations and to an increased extinction

risk to the remaining populations. Furthermore,colonization rates may be reduced in isolated

patches (Soons and Heil 2002; Joshi et al. 2006).

Intuitively, forests fragmented by anthropogenic

sources are at a higher risk of further fragmenta-

tion or removal than forests fragmented by nat-

ural causes. This isolation of forest patches leads

to the negative impact on the stand regeneration

and also adversely affects the survival of species,

which require contiguous forest patches for their

survival and regeneration (Niemi 1998; Laurance

et al. 1998a, b, 2002). Most of the disturbance to

the forest patches is as a result of indirect anthro-

pogenic pressure rather than direct encroachment

or clear felling. This is indicated by the significant

increase in the FD, which is a representation of 

patch shape complexity (Krummel et al. 1987;

Díaz-Delgado et al. 2004). Identifying man-made

forest fragmentation may be a useful tool for pol-

icy and decision makers, allowing for improved

risk assessments and better targeting of areas for

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Table 8 Ten dominant IVI species in different fragment classes for the evergreen and semi-evergreen forest of SouthernWestern Ghats (India)

Interior Patch Others

Evergreen forest

Cullenia exarillata* 28.20 Cullenia exarillata* 21.93 Cullenia exarillata* 31.22

  Agrostistachys meeboldii 13.32 Dimocarpus longan* 19.78 Dimocarpus longan* 20.19

Syzygium gardneri 9.90 Euodia lunu-ankenda* 7.87 Meliosma pinnata 7.62

Myristica dactyloides* 9.72 Acronychia pedunculata 7.77 Myristica dactyloides 7.27Mesua ferrea* 9.58 Diospyros foliolosa 6.81 Schleichera oleosa 7.22

Hopea utilis 9.46 Sageraea laurifolia 6.63 Pterospermum xylocarpum 6.73

  Aglaia bourdillonii* 8.96 Hopea parviflora* 6.61 Mesua ferrea 5.94

Calophyllum austroindicum 6.91 Mesua ferrea* 6.32 Calophyllum austroindicum* 5.36

Dimocarpus longan 6.77 Mallotus philippensis 5.86 Antidesma menasu* 4.92

Palaquium ellipticum* 5.63 Hopea ponga 5.32 Tricalysia apiocarpa* 4.55

Semi-evergreen forest

Mesua ferrea* 15.51 Dimocarpus longan* 28.96 Hopea parviflora* 23.07

Dimocarpus longan* 11.11 Kingiodendron pinnatum* 22.01 Syzygium mundagam* 15.77

Kingiodendron pinnatum 9.13 Filicium decipens* 19.29 Diospyros paniculata* 14.75

Canarium strictum 6.93 Vitex altissima 15.06 Alstonia scholaris 13.56

Scolopia crenata 6.24 Phoebe wightii* 13.51 Wrightia tinctoria 12.65  Xanthophyllum flavescens* 6.11 Holigarna arnottiana* 10.33 Eugenia thwaitesii* 11.97

Myristica dactyloides* 6.05 Acronychia pedunculata 10.20 Dimocarpus longan* 11.66

Syzygium gardneri 5.32 Scolopia crenata 9.84 Garcinia gummi-gutta 11.57

Symplocos macrocarpa 5.31 Syzygium caryophyllatum 8.88 Acronychia pedunculata 10.54

Schleichera oleosa* 5.25 Symplocos macrocarpa 8.72 Alangium salvifolium 8.94

*Observed species dominant in the structure of the forest during field observation

protection or remediation. The method presented

produces data that may be summarized and dis-

played in a myriad of ways, each of which may be

useful to the decision process.Patch characteristics of 1973 were significantly

different in terms of size, proportion, shape, and

context from those of 2004 because of type tran-

sition like evergreen to semi-evergreen, expan-

sion of  Ochlandra and orchards. The variation

in the physical environment viz., climate, soil,

topography, and other landform features might

have led to heterogeneous spatial distribution of 

resources like water, nutrients, and light resulting

in the formation of vegetation patches of differ-

ent characters (Kolasa and Pickett 1991; Burnettet al. 1998; Nichols et al. 1998; Peters and Goslee

2001). In addition, naturally occurring and man-

made disturbances also play a vital role in the

patch formation and characteristics (Platt 1975;

Fuller et al. 1998). Factors such as wildlife grazing,

wildlife movement, fuel-wood extraction, fire, and

collection of honey and nontimber forest products

by local people are also prevalent in different

degrees of biotic pressure. The extent of forest

and commercial plantation activities and the pro-

tection and conservation measures followed in the

area also vary in degree and kind.

Remarkably, the contiguous patches of >1,000 ha covered 90% of evergreen forest in

1973 and had less porosity where plantations

and anthropogenic pressures are minimal when

compared to the data of 2004 which showed a high

level porosity of 67%, probably due to Ochlandra

spread and increased plantations which resulted

in the loss of such contiguous patches. The

focused priority on conservation of these patches

may be helpful to sustain biological diversity, as

these patches of evergreen forests provide unique

habitats for various endemic plant species andwildlife. These patches may be large enough to

allow the natural disturbance regime to operate,

maintain characteristic species composition, sup-

port mosaics of community formations, and sus-

tain successional patterns and system functions

(Pickett and Thompson 1978). The increase

in the FD also point out to the fact that the

KMTR is constantly under indirect pressure due

to the surrounding biotic or climatic/edaphical

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conditions. Despite legal protection from major

human activities, the region is subjected to various

processes that ultimately prove detrimental to

the sustenance of the native forest system. In this

context, the moderate spatial and high spectral

resolution data from wide field sensors can be

used for the generation of extensive informationregarding vegetation area, patch shape and size,

fragmentation patterns, and porosity, which

are the major indicators of the disturbance and

land-use change in a region.

Patch analysis thus provides a simple frame-

work for goal-oriented monitoring and manage-

ment in a forest landscape that has experienced

several degenerative trends, i.e., primary ever-

green forests have been replaced by semi-

evergreen forests and plantations; structurally

complex forests of all ages have been replacedby simplified stands; large, well-connected patches

have been replaced by smaller, more isolated

patches; infrastructure has been developed in

undisturbed landscapes; and natural fires have

been suppressed. Several forests in Western Ghats

and elsewhere in the tropics have experienced

these kinds of changes with a concomitant loss

of native biodiversity and ecological integrity

(Dutt et al. 2002; Muthuramkumar et al. 2006).

It is commonly accepted that species richness re-

duces with the fragmentation of tropical forests(Lovejoy et al. 1986; Bierregaard et al. 1992;

Chittibabu and Parthasarathy 2000; Benitez-

Malvido and Martinez-Ramos 2003; Laurance

and Luizão 2007). The smaller the fragments

are, the less species richness the fragments

display (Newmark 1991; Leigh et al. 1993;

Laurance 1994; Pither and Kellmann 2002).

Research articles related to forest fragments

that are published elsewhere mostly focus on

various animal groups. Studies on plants re-

lated to tropical forest fragments are relatively

fewer, although there have been some impor-

tant ones (Leigh et al. 1993; Turner and Corlett

1996; Oliveira-Filho et al. 1997; Benitez-Malvido

1998; Laurance et al. 1998a, b; Cadotte et al.

2002; Benitez-Malvido and Martinez-Ramos 2003;

Muthuramkumar et al. 2006; Laurance and Luizao

2007).

Temporal variation in species diversity can be

strongly associated to external disturbances (Holt

and Lawton 1994; Chesson et al. 2004). Distur-

bances like deforestation, fire, and harvest of se-

lective species can strongly influence patterns of 

species diversity. A buffer of 100 m was ana-

lyzed on selected patches to understand the bi-

otic pressure (e.g., orchards, secondary formations

like reeds and semi-evergreens) and exchangesamong patches, which determine the structure and

function of the ecosystem. It reveals that 6.38%

of evergreen and 5.13% of semi-evergreen forest

have undergone several changes over the period

between 1973 and 2004. Other similar attempts

were carried out to understand the patch dy-

namics and biotic exchanges among patches and

to determine the ecosystem structure and func-

tion (Lewin 1984; Nagendra 2001). High diversity

relationships can be explained by the character-

istics of the community, the habitat, the distur-bance, and the sampling designs (Reice 1985;

Noss 1996; Huston 1994; Mackey and Currie 2000,

2001; Girira j 2006). In the present study, we have

focused on the impact of strong local interac-

tions and the increased importance of regional-

scale processes of dispersal among the patches

in controlling the number of species within a

patch. Other similar case studies include those of 

Caswell and Cohen (1993), Mouquet et al. (2003),

Mouquet and Loreau (2003), and He et al. (2005).

In this connection, the spatial organization of thepatches as identified in the study can form a base-

line for continuous monitoring and assessment of 

the changes in habitat conditions.

Thus, the fragmentation index provides a useful

tool for monitoring the changes in the species

structure and pattern over time. High species rich-

ness and stand density was observed in the interior

forest than in the patches and perforated systems

(Table 7 and Fig. 3). Similarly, the species com-

position and abundance in the fragment class of 

the evergreen forest had made more changes in

community structure than in the interior category

leading to the replacement of habitat specialist

species. The saplings in the evergreen forests of 

the interior category had lesser stand density than

the fragment classes. This might be due to the

prevalence of secondary and successional species

like Clerodendron, Macaranga, and Mallotus and

the creation of large gaps within the patches,

which resulted in the formation of deciduous

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and other invasive species. Thus, ecology of the

species groups changed conspicuously with the

increase of forest fragments. The heliophilous or

pioneer tree species increased and the shade-

tolerant species reduced in the fragmented forests.

The increased seedling ratio of edge individuals

and the reduced level of endemics in the changeareas indicate the probability of further transitions

that may occur over the coming decades. The

present study of forest fragments using remote

sensing-based identification in temporal time, in

combination with landscape metrics and phytoso-

ciological inputs, has helped in delineating areas

of biodiversity conservation and prioritization.

Our recommended solution to prevent the loss

of species is to establish a network of large pro-

tected areas throughout the tropics (Peres 1994).

While this is an important goal, some tropicalregions have lost so much of their forest cover that

there are very few large forest patches remaining

(Turner and Corlett 1996). Those large forested

areas should remain priorities for conservation

(Ghazoul 1996; Gascon et al. 2000), but it is also

important to consider the potential role of the

other, smaller forest patches which often consti-

tute a large number of the remaining patches in

disturbed tropical landscapes.

Acknowledgements This research was supported by theproject DBT-DOS Biodiversity characterization at land-scape level in the Western Ghats using remote sensingand GIS. We are thankful to the Forestry and EcologyDivision, National Remote Sensing Centre and anonymousreviewers for the helpful comments.

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